Examining the Relationship Between Environmental Factors and Inpatient Hospital Falls: Protocol for a Mixed Methods Study - JMIR Research Protocols
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JMIR RESEARCH PROTOCOLS Shorr et al
Protocol
Examining the Relationship Between Environmental Factors and
Inpatient Hospital Falls: Protocol for a Mixed Methods Study
Ronald I Shorr1*, MD, MS; Sherry Ahrentzen2*, PhD; Stephen L Luther3*, PhD; Chad Radwan3*, PhD; Bridget Hahm3*,
MA, MPH; Mahshad Kazemzadeh2*, PhD; Slande Alliance4*, MPH, MCHES; Gail Powell-Cope4*, PhD; Gary M
Fischer5, MArch
1
Geriatric Research Education and Clinical Centers, North Florida/South Georgia Veterans Health System, Gainesville, FL, United States
2
Shimberg Center for Housing Studies, College of Design, Construction and Planning, University of Florida, Gainesville, FL, United States
3
Research Service, James A Haley Veterans Hospital, Tampa, FL, United States
4
Research Service, North Florida/South Georgia Veterans Health System, Gainesville, FL, United States
5
Office of Facilities Standards Service/Office of Facilities Planning, Office of Construction and Facilities Management, Department of Veterans Affairs,
Washington, DC, United States
*
these authors contributed equally
Corresponding Author:
Mahshad Kazemzadeh, PhD
Shimberg Center for Housing Studies
College of Design, Construction and Planning
University of Florida
1480 Inner Road
Gainesville, FL
United States
Phone: 1 352 317 8172
Email: m.kazemzadeh@ufl.edu
Abstract
Background: Patient falls are the most common adverse events reported in hospitals. Although it is well understood that the
physical hospital environment contributes to nearly 40% of severe or fatal hospital falls, there are significant gaps in the knowledge
about the relationship between inpatient unit design and fall rates. The few studies that have examined unit design have been
conducted in a single hospital (non-Veterans Health Administration [VHA]) or a small number of inpatient units, limiting
generalizability. The goal of this study is to identify unit design factors contributing to inpatient falls in the VHA.
Objective: The first aim of the study is to investigate frontline and management perceptions of and experiences with veteran
falls as they pertain to inpatient environmental factors. An iterative rapid assessment process will be used to analyze the data.
Interview findings will directly inform the development of an environmental assessment survey to be conducted as part of aim
2 and to contribute to interpretation of aim 2. The second aim of this study is to quantify unit design factors and compare spatial
and environmental factors of units with higher- versus lower-than-expected fall rates.
Methods: We will first conduct walk-through interviews with facility personnel in 10 medical/surgical units at 3 VHA medical
centers to identify environmental fall risk factors. Data will be used to finalize an environmental assessment survey for nurse
managers and facilities managers. We will then use fall data from the VA Inpatient Evaluation Center and patient data from
additional sources to identify 50 medical/surgical nursing units with higher- and lower-than-expected fall rates. We will measure
spatial factors by analyzing computer-aided design files of unit floorplans and environmental factors from the environmental
assessment survey. Statistical tests will be performed to identify design factors that distinguish high and low outliers.
Results: The VA Health Services Research and Development Service approved funding for the study. The research protocol
was approved by institutional review boards and VA research committees at both sites. Data collection started in February 2018.
Results of the data analysis are expected by February 2022. Data collection and analysis was completed for aim 1 with a manuscript
of results in progress. For aim 2, the medical/surgical units were categorized into higher- and lower-than-expected fall categories,
the environmental assessment surveys were distributed to facility managers and nurse managers. Data to measure spatial
characteristics are being compiled.
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Conclusions: To our knowledge, this study is the first to objectively identify spatial risks for falls in hospitals within in a large
multihospital system. Findings can contribute to evidence-based design guidelines for hospitals such as those of the Facility
Guidelines Institute and the Department of Veterans Affairs. The metrics for characterizing spatial features are quantitative indices
that could be incorporated in larger scale contextual studies examining contributors to falls, which to date often exclude physical
environmental factors at the unit level. Space syntax measures could be used as physical environmental factors in future research
examining a range of contextual factors—social, personal, organizational, and environmental—that contribute to patient falls.
International Registered Report Identifier (IRRID): DERR1-10.2196/24974
(JMIR Res Protoc 2021;10(7):e24974) doi: 10.2196/24974
KEYWORDS
falls; accidental falls; hospital design and construction; health facility environment; hospital units; evidence-based facility design;
nursing; environmental factors; well-being; accident
visibility from decentralized nurses’ stations and from corridors
Introduction was significantly associated with the incidence of patient falls.
Background As part of our mixed methods study, we propose a similar
approach to physically measure environmental design factors
According to the Joint Commission, patient falls are within Department of Veterans Affairs (VA) hospitals that may
hospital-acquired conditions, and falls with serious injury were contribute to patient falls via the manner in which design affects
the most reported sentinel event in 2018 [1]. Inpatient falls result accessibility and visibility. It should be noted that this does not
in a financial burden to US medical organizations, contributing include video monitoring as it may not be not allowed in
to a 61% increase in patient care costs [2] and decreased quality medical/surgical units. The physical design of a unit can
of life for the injured patients. In 2015, the total medical costs facilitate or impede nursing care, affecting efficiency, stress,
for falls totaled more than $50 billion, and Medicare and and patient care [10]. Hospital unit design experts often ask if
Medicaid shouldered 75% of these costs [3]. Thus, decreasing the design is (1) flexible, allowing for changes over time, (2)
the rate of patient falls is a main focus for improving the quality efficient, allowing for quick and easy access to patients, families,
of health care. According to the Joint Commission, physical computers, and supplies, (3) permitting the most optimal use
environment was a common factor contributing to a fall with of the space while increasing unimpeded sight lines, and (4)
injury [4]. Although programs that address multiple risk factors welcoming to patients and their families.
have been implemented to reduce hospital falls, none of the
commonly used fall risk assessment tools include built Data on falls and fall-related injuries have been systematically
environment factors [5]. Retrospective research studies collected and analyzed for all nonfederal hospital units since
examining the association between the physical environment 2011. Although the complementary data sources exist for
of the hospital unit and patient falls are few [6], and many of Veterans Health Administration (VHA) hospitals, there are only
these rely on Likert-type scales of perceived intensity (eg, a few published studies describing the system-wide burden of
excellent to poor lighting or sight lines) rather than physical hospital falls in the VHA system of care [11,12]. In the past
measurement of environmental factors (eg, lumens, distance in decade, hospital and health care design is increasingly guided
linear feet). Many of these studies narrowly focus on design by evidence-based design and rigorous research to link the
factors immediately impinging on the patient (eg, bedrails) [7] spatial design and built characteristics of hospitals to health
and overlook how physical design affects workflow and care care outcomes [5,13].
delivery, which in turn affects patient outcomes such as falls Study Objectives
[5,8].
This mixed methods study will explore the relationship between
Factors in the facility environment that affect social organization unit design and patient falls in VHA medical/surgical units. The
and behavior include spatial organization, environmental goal of aim 1 is to investigate frontline staff and management
systems, communication cues, ambient qualities, and perceptions of and experiences with veteran falls as they pertain
architectural details [9]. Of these, spatial organization factors to inpatient environmental factors including patient rooms,
play a prominent role in supporting or hindering behaviors of bathrooms, nurses’ stations, and hallway design features. We
staff and patients in health care settings. Corridor layout, the will conduct walk-through interviews in medical/surgical units
location of nursing stations, and placement of interior doors and at 3 VHA medical centers with unit and facility personnel to
windows can facilitate or impede staff oversight of patient identify environment-related fall risk factors for patient falls.
movement and activities. In one hospital case study, Choi [6] Interview findings will be used to develop an environmental
examined the locations of patient falls in relation to physical assessment survey to be conducted as part of aim 2. The goal
accessibility and visibility from nurse to patient bed using key of aim 2 is to quantify unit design factors and compare spatial
locations (nursing station, medications, and a corridor’s and environmental factors of units with higher- versus
circulation path). Using digitized floor plans and spatial analysis lower-than-expected fall rates. We will use fall data from the
software, Choi numerically and graphically analyzed physical VA Inpatient Evaluation Center and patient data from additional
accessibility and visibility (ie, sight lines) from key locations data sources to identify units with higher- and
to inside patients’ rooms. Findings showed that patient bed lower-than-expected risk-adjusted fall rates. Predicted values
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for hospital fall rates will be based on a regression model by investigate staff and management perceptions of environmental
using the SAS Proc Mixed procedure employing residual factors that contribute to patient falls (aim 1). We will use
(restricted) maximum likelihood covariance structure and quantitative approaches to identify medical/surgical units with
accounting for nesting within Veterans Integrated Service higher- or lower-than-expected fall rates and identify spatial
Networks (VHA region) and facility [14]. Differences between and environmental factors that distinguish them (aim 2).
predicted and observed values will be based on studentized
The study conceptual framework is based on the box model
residuals. We will measure spatial factors by analyzing
proposed by Tzeng [15], which acknowledges that fall
computer-aided design (AutoCAD) files of unit floorplans and
prevention encompasses patient-, unit-, and facility-level system
environmental factors based on the environmental assessment
risk factors (Figure 1). Patient-level characteristics include
survey.
factors like age, gender, severity of illness/comorbidities,
surgical procedures, psychotropic drugs, and altered mental
Methods status. Unit-level characteristics include nurse staffing, type of
Design additional unit level and patient room characteristics such as
unit accessibility, unit visibility, corridor path length, distance
We propose a mixed methods descriptive study to explore the from bed to bathroom, and patient room type. Facility-level
relationship between unit design and patient falls in VHA characteristics include facility complexity and geographic
medical/surgical units. We will use a qualitative approach of location.
participant observation with walk-through interviews to
Figure 1. Conceptual model.
at least 1 year of hospital experience at the hospital where they
Setting and Study Population are currently employed. Both day and night shift staff will be
The VA is the largest integrated health care system in the United recruited.
States, consisting of 150 medical centers, nearly 1400
community-based outpatient clinics, community living centers, From all medical/surgical units in the VHA system, we will
Vet Centers and domiciliaries. Together, these health care identify nursing units reporting unusually high and low patient
facilities and the more than 53,000 independent licensed health fall rates over time (ie, nursing units showing highest deviation
care practitioners who work in them provide comprehensive from the rates predicted by an appropriately fitted regression
care to more than 9 million veterans each year [16]. model that includes the known standard predictors of patient
falls) [17]. To simplify modeling, we will use aggregated
Inclusion Criteria measures of 48 months of observation. Nursing units that report
Within each facility, personnel at 4 different organizational extreme risk-adjusted fall rates may constitute interesting
levels and in different roles will be invited to participate. outliers that are not statistical nuisances but which can be used
Participants will be nurse managers, staff nurses, patient care to gain a deeper understanding of the underlying processes
technicians, occupational and physical therapists, and Patient leading to patient falls [12].
Safety Committee members currently working in
medical/surgical units at the facilities. Participants should have
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Study Procedure Aim 1: Participant Observation approach that provides an opportunity to uncover participants’
perspectives using a conversational style.
Recruitment and Enrollment
We will recruit a purposive [18] sample of clinical staff. We Interview Guide
will ask the nursing service administrator at each facility to We developed a semistructured interview guide to elicit
identify nurse managers of the chosen units and work with the responses from all staff participants regarding hospital falls
nurse managers to identify individual staff. While identifying (Multimedia Appendix 1). The interview guide was designed
staff through administrators and managers may introduce bias, to elicit perceptions and ideas related to unit design factors and
we have used this method successfully in VHA hospitals and their interactions with facility and patient factors that increase
have found staff to be forthcoming in responses to interview the risk of falls. Examples of interview questions include the
questions and questionnaires. The unions at each facility following:
endorsed this recruitment method. Once potential interview • What factors at this hospital influence the risk of inpatient
participants have been identified, project team members will falls?
contact each in person or by email or telephone and explain the • What efforts are being made at the leadership level to
project. The project manager will explain the informed consent change these factors?
with audio addendum process to each potential participant and, • Do you think unit design has an impact on how staff are
if agreeable, send them the informed consent form. able to see patients as they ambulate or get out of their beds?
Walk-through interviews will be scheduled in accordance with • As we walk through the unit, please describe where a patient
facility and union standard operating procedures and regulations. fall occurred and whether you thought the layout of the unit
We will schedule the interviews at times that are convenient or patient room influenced the fall or its outcome.
for participants and hospital unit workflow.
Data Management
Interview Procedures
To ensure data quality of walk-through interviews, (1)
We will conduct 10 walk throughs in 3 facilities yielding 10 experienced facilitators will conduct the interviews; (2) data
group interviews with a total of up to 35 participants. analysis will be concurrent with data collection, and participant
Walk-through interviews are a data gathering technique feedback will be assessed and compiled; (3) interviews will be
frequently used in architectural programming to build audiorecorded to ensure that no information is missed; (4)
postoccupancy evaluation. In the walk-through interview, photographs will be labeled with interview time, location, and
observation and interviewing take place simultaneously. The corresponding statements referencing design factors of interest;
interviewer walks through designated areas of the building under and (5) data analysis will be conducted by one investigator and
study with a small group of building occupants. As they walk the qualitative data manager. Additionally, an assistant facilitator
from area to area, questions are posed by the interviewer, will take notes and debrief with the facilitator after the
eliciting discussion of key issues, problems, and benefits as interviews to record shared or unique perspectives. The
perceived by occupants. By coupling the interview with qualitative data manager will manage data files and organize
observation of the setting, the walk through triggers detailed and assist with data coding. Interview recordings will be
recalls of experiences and reactions as related to building factors. reviewed by both facilitators to verify accuracy of field notes
This approach allows investigators to triangulate direct and add missing data. Data will be secured and backed up behind
observation of the physical factors of the hospital unit with the the password-protected VA firewall with access limited to team
subjective perspective of the occupant regarding situations members. Investigators will meet regularly to debrief on data
associated with it. methodologies, data integrity, and data security.
The interview team will include (1) a facilitator skilled in
Data Analysis Plan
qualitative methods who will lead discussions using an interview
guide, (2) an assistant facilitator who will take photographs of Analysis of interview data will begin following the first
environmental conditions, and (3) subject matter experts from interview and will be performed concurrently with ongoing
the study team who will be primarily nonparticipant observers. interviews as transcripts are obtained. Insights obtained from
Interviews will be audiorecorded on password-protected and continuous analysis will be used to guide further data collection
encryption-capable digital recorders with high-quality audio. by modifying the interview guide, understanding feedback from
Participants will complete an anonymous questionnaire to participants, and conceptualizing provisional results. A rapid
summarize demographics of the group. At the start of the assessment process, an “intensive, team-based, qualitative
walk-through interview, the purpose will be explained and any inquiry using triangulation, iterative data analysis, and additional
questions from participants will be answered. Participants will data collection to quickly develop a preliminary understanding
be told that their responses will be presented in aggregate or an of a situation from the insider’s perspective” [19], will be used
otherwise deidentified manner and that the interview discussions to analyze the data. This analysis [20] emphasizes speed of data
will remain confidential. Standard response-eliciting techniques collection and analysis to focus on programmatic questions or
will facilitate discussion using generic prompts (eg, “tell me problems encountered by health services researchers.
more”), summarizing statements, asking for similar and Triangulation of data will be facilitated by including staff who
contrasting opinions, controlling overtalkers, and including all hold different roles, using photographs to validate interviewee
participants in the discussion. The facilitator will use a flexible responses and collecting data on different units in different
hospitals. Interview notes and transcripts will be reviewed by
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the data team for inductive data reduction to sort, focus, and t test, the standard deviations were assumed to be unknown and
organize data so themes can be identified and conclusions equal. The second sample size calculation was based on a
obtained [20]. Domain names will be developed to correspond 1-degree of freedom chi-square test. A 2-sided alpha level of
with interview questions, and a summary template will be .50 was used in both calculations.
created. Prior to analysis, the template will be internally tested
by the team for usability and reliability. Several team members
Study Procedure Aim 2: Linking Unit Design and Falls
will summarize transcripts and transfer the themes into a matrix Procedures
to synthesize important findings.
To gather data on spatial and environmental characteristics of
Study Procedure Aim 2: Modeling Falls Data the units and patient rooms, we will contact facility managers
of the sampled hospitals to request AutoCAD digitized
Procedures documents of floor plans and interior sections of the designated
We will obtain the studentized residuals, the difference between unit and completion of the environmental assessment survey
the observed data and the predicted value of the observation, by nurses and facilities management staff developed during aim
based on the model fitted as described below. The top and 1 that includes design features not available on AutoCAD
bottom 25 units (n=50) according to the ranked studentized documents (Multimedia Appendix 3). Efforts to maximize
residuals will be selected to form high and low comparison cooperation and participation by nurse managers and facilities
groups in the second phase. The use of residuals to classify units management will include (1) an email request explaining the
as high versus low fall rates implies that the amount of study and study findings as highly relevant because they reflect
unexplained variance is higher or lower than expected after evidence-based design objectives called for by the VA Office
adjusting for available known factors. For example, a unit with of Construction and Facilities Management, (2) request cosigned
the highest predicted adjusted rate may not qualify to be in the by the principal investigator and VA Senior Healthcare
unusually high group because it was accurately predicted by Architect, (3) follow-up email requests, (4) collaboration with
the multivariable model; the difference between predicted and the VHA Office of Nursing Service, and (5) follow-up for
observed rates would be relatively small. Alternately, if a nonresponders.
medium rate is predicted for a unit but the observed rate is
AutoCAD documents are digitized files of floor plans and
unexpectedly high, this would be regarded as an unusually high
interior sections of the hospital units. Many spatial features (eg,
value.
walls, doors, interior and exterior windows, counter heights)
To develop the models, we will use the most recent national and functional locations (eg, nurses’ stations, medication rooms)
VHA falls data based on the start date of the study, fiscal years are contained in these documents. Project team members will
2013-2017. To provide an estimate of available data for the be blinded to whether the floor plans come from high-fall or
study, we accessed unit-level fall data for all medical/surgical low-fall units.
units through the VHA Support Service Center (317 units and
12,531 unit months). After excluding units with fewer than 3
Spatial Analysis
or more than 200 patient days per month, 11,532 patient months Space syntax metrics will be computed indirectly by Depthmap
were available for analysis. Multimedia Appendix 2 summarizes software analysis using spatial data entered directly from
the definitions and sources for each of these variables, grouped AutoCAD files. Depthmap is a single software platform that
by model domains. performs spatial network analyses (ie, space syntax) [21,22]
using maps of the spatial layout of the hospital unit based on
Data Analysis Plan user-designated points within units. Depthmap operates by
To develop models, we will investigate the patterns of fall rates performing a set of spatial network analyses. One set uses
per unit per month across 60 months. The degree of variability visibility graph analysis [22]. A grid of points is overlaid on a
or stability in rates will guide how to aggregate the falls data. floor plan where each point is connected to every other point
Mean fall rates and risk measure scores will be included in a that it can see. The visual integration of a point is based on the
linear mixed model using SAS (SAS Institute Inc) statistical number of steps it takes to get from that point to any other point
software. The facility identifier will be treated as a random within the network. Various graph measures and ratio-level
effect (to adjust for nesting of data within facilities), with all metrics can be calculated, depending upon the research
other predictors as fixed effects. We will review regression hypotheses [23,24].
statistics on the basis of how well the regression model predicts
Physical and design characteristics data will be extracted directly
the dependent variable of fall rates.
from AutoCAD files and environmental surveys. Some physical
Power Analysis and design characteristics (eg, distance from patient bed to
Statistical testing will be conducted to compare unit design patient bathroom) will be calculated within the AutoCAD
variables between units identified with risk-adjusted high-fall program itself (Multimedia Appendix 4). Use of AutoCAD files,
and low-fall rates. Estimated sample sizes (number of nursing environmental surveys, and Depthmap reduces the need for
units) required to achieve 80% statistical power and the extensive on-site measurement by hospital staff or researchers.
corresponding minimum detectable effect sizes range from a This methodology ensures reliability of data collection across
low of 40 (20 high-fall and 20 low-fall) to a high of 50 (25 sites and minimizes measurement error that occurs by direct
high-fall and 25 low-fall). In the sample size calculation for the measurement.
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Statistical Analysis of falling and using clinical judgment to decide which of a
Statistical and graphic comparisons will be made between myriad of strategies will reduce fall risk [29]. A quantitative
high-fall and low-fall units for the variables in Multimedia review found no evidence of benefit among published
Appendix 4. The presence of statistically significant associations nursing-oriented hospital fall prevention studies using concurrent
between hospital unit fall category (high, low) and each unit controls (incidence rate ratio 0.92; 95% CI 0.65-1.30) [30,31].
design measure will be tested separately as follows: a 2-sample Even though tremendous resources have been dedicated to
t test for continuous measures (accessibility, visibility, corridor reduce falls in VHA hospital units, a wide variation in fall rates
length) and a chi-square test for categorical measures (ie, single still occurs. The advantages of the proposed research design are
versus multioccupancy patient rooms). that it leverages the power of large VA administrative databases
to identify nursing units that have the highest and lowest
Ethical Approval and Consent to Participate risk-adjusted fall rates and conducts in-depth analyses using
The research protocol was approved by the University of Florida physical measurements of environmental factors to identify
and University of South Florida institutional review boards and factors contributing to fall rates. We will employ a novel
VA Research Committees at both sites. Local union approval analysis of floor plans using Depthmap spatial software to
was obtained to conduct the walk-through interviews, and investigate unit design factors between the units with high and
written informed consent was obtained before the interviews. low fall rates. These space syntax measures could be used as
VHA Labor Relations and the National Nurses Union reviewed physical environmental factors in future research examining a
the protocol and instruments and provided concurrence to range of contextual factors—social, personal, organizational,
conduct the nurse environmental assessment survey. The and environmental—contributing to patient falls. In addition,
environmental assessment surveys were emailed; a waiver of the findings from this study can contribute to development and
documentation of informed consent was approved as the refinement of evidence-based design guidelines for hospitals
completion of the survey implied consent. Approved informed and health care settings such as those of the Facility Guidelines
consent language was included on the first page of the Institute and the VA.
environmental assessments. Study Limitations
Results The walk-though portion of the study had 3 limitations we
attempted to minimize through design of the study. First, the
All study approvals were obtained by January 2018. From facilities selected for walk-through interviews formed a
January to March 2019, we conducted walk-through interviews convenience sample, so they may not be representative of all
and finalized the environmental assessment survey. By VHA medical/surgical units. Given that the facilities available
November 2019, we identified 25 units with were built or renovated during different time periods, they
higher-than-expected fall rates and 25 units with provided for variations that may exist across the VHA. Second,
lower-than-expected rates. In January 2020, we began to request because units are very busy places with high demands on staff,
AutoCad files from these units. In January and August 2020, we included multiple staff so that if one was called away the
we surveyed facilities managers and nurse managers, walk throughs could be completed without them. Staff not in
respectively. We expect to complete data analysis by February the walk throughs covered their absences as they were able.
2022. Dissemination will occur during the following year. Third, because walk-through interviews included managers and
frontline staff, we were aware of the potential for group
Discussion dynamics being influenced by power differentials. The research
team used validated focus group techniques to elicit feedback
Principal Findings from all participant such as calling on individuals who were not
Patient falls are the most common adverse events reported in as likely to offer responses as others.
hospitals [1,25]. Although it is well understood that the physical Three limitations were noted for aim 2. First, each unit had only
hospital environment is a common contributing factor to falls one participant per unit completing the environmental
with injuries [26], there are significant gaps in our knowledge assessment survey, increasing the possibility of bias responses.
about the relationship between inpatient unit design and fall To minimize this bias, we asked nurse managers, who are highly
rates. The few studies that have examined unit design have been knowledgeable decision makers, to complete the surveys.
conducted in a single hospital or a small number of inpatient Second, the risk adjustment models were complex and built on
units, limiting generalizability [27,28]. Furthermore, no studies data from multiple data sources. While the VHA is an integrated
have focused on unit design and falls in VHA medical centers. health care system, we were faced with linking data that have
Thus, the overarching goal of this study is to identify unit design no formal common identifying codes. All information available
factors contributing to inpatient falls within the VHA. in each data source was used to match the units, and we
Study Strengths conducted validity checks across datasets. Third, use of space
syntax analysis requires some assumptions (eg, height of the
To our knowledge, this study represents the first attempt to agent line of sight). In this study, we considered that nurses are
study hospital falls in a large multihospital system. Hospitals sitting in the nursing station and have a 360° view of their
employ numerous approaches to develop fall prevention policies. surroundings. However, they may be in the nursing station
In general, the procedures are largely directed at nursing performing administrative tasks and not observing patients.
techniques and include identifying patients who are at high risk Also, nurses are not always sitting in the nursing station; they
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might be walking in the corridor, which requires the assumption Institute and the VA. The metrics for characterizing spatial
of standing height for the line of sight. features are quantitative indices that could be incorporated in
larger scale contextual studies examining contributors to falls,
Conclusions which to date often exclude physical environmental factors at
To our knowledge, this study is the first to objectively identify the unit level. Space syntax measures could be used as physical
spatial risks for falls in hospitals within a large multihospital environmental factors in future research examining a range of
system. Findings can contribute to evidence-based design contextual factors—social, personal, organizational, and
guidelines for hospitals such as those of the Facility Guidelines environmental—that contribute to patient falls.
Acknowledgments
This work was supported by Merit Review Award #1 I01 HX002191-01 and grant number IIR 16-063 from the VA Health
Services Research and Development Program. This work was supported by resources provided by the North Florida/South Georgia
Veterans Health System, Gainesville, FL, and James A Haley Veterans Hospital in Tampa, FL. The contents of this manuscript
do not represent the views of the VA or the United States Government.
Authors' Contributions
All authors were involved in the design of the study. GPC was responsible for drafting and editing the manuscript. All authors
provided significant edits and comments, read drafts, and approved the final version of the manuscript.
Conflicts of Interest
RIS serves as an expert witness in cases of hospital falls. All other authors declare no conflicts of interest.
Multimedia Appendix 1
Walk-through interview guide.
[PDF File (Adobe PDF File), 117 KB-Multimedia Appendix 1]
Multimedia Appendix 2
Variables for creating models to identify fall rates that are higher and lower than expected.
[DOCX File , 15 KB-Multimedia Appendix 2]
Multimedia Appendix 3
Nurse environmental assessment survey.
[PDF File (Adobe PDF File), 680 KB-Multimedia Appendix 3]
Multimedia Appendix 4
Spatial and environmental variables.
[DOCX File , 14 KB-Multimedia Appendix 4]
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Abbreviations
AutoCAD: computer-aided design
VHA: Veterans Health Administration
VA: Department of Veterans Affairs
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Edited by G Eysenbach; submitted 28.10.20; peer-reviewed by M Stein, C Miranda; comments to author 19.12.20; revised version
received 02.02.21; accepted 17.03.21; published 13.07.21
Please cite as:
Shorr RI, Ahrentzen S, Luther SL, Radwan C, Hahm B, Kazemzadeh M, Alliance S, Powell-Cope G, Fischer GM
Examining the Relationship Between Environmental Factors and Inpatient Hospital Falls: Protocol for a Mixed Methods Study
JMIR Res Protoc 2021;10(7):e24974
URL: https://www.researchprotocols.org/2021/7/e24974
doi: 10.2196/24974
PMID: 34255724
©Ronald I Shorr, Sherry Ahrentzen, Stephen L Luther, Chad Radwan, Bridget Hahm, Mahshad Kazemzadeh, Slande Alliance,
Gail Powell-Cope, Gary M Fischer. Originally published in JMIR Research Protocols (https://www.researchprotocols.org),
13.07.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License
(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information,
a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be
included.
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